39efccc696a1c20745a52cc50935cdc24f92230d,secuml/core/classif/classifiers/__init__.py,Classifier,_predict_streaming,#Classifier#,146

Before Change

            if matrix is None:
                matrix = [row]
            else:
                matrix = np.vstack((matrix, row))
            if num_rows >= stream_batch:
                ids = instances_ids.get_from_ids(ids)
                predictions = self._update_streaming_predictions(predictions,
                                                                 matrix, ids)

After Change

        num_batches = instances_ids.num_instances() // stream_batch
        num_remaining = instances_ids.num_instances() % stream_batch
        for i, batch in enumerate(range(num_batches)):
            matrix = np.vstack(tuple(next(features_iter)
                                     for _ in range(stream_batch)))
            ids = instances_ids.ids[i*stream_batch:(i+1)*stream_batch]
            ids = instances_ids.get_from_ids(ids)
            predictions = self._update_streaming_predictions(predictions,
                                                             matrix, ids)

Instances